The Determinants behind the Acceptance of Autonomous Vehicles: A Systematic Review

Peng Jing, Gang Xu, Yuexia Chen, Yuji Shi and Fengping Zhan
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Peng Jing: School of Automobile and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China
Gang Xu: School of Automobile and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China
Yuexia Chen: School of Automobile and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China
Yuji Shi: School of Automobile and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China
Fengping Zhan: School of Automobile and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China

Sustainability, 2020, vol. 12, issue 5, 1-26

Abstract: Excessive dependence on autonomous vehicles (AVs) may exacerbate traffic congestion and increase exhaust emissions in the future. The diffusion of AVs may be significantly affected by the public’s acceptance. A few factors that may affect people’s acceptance of AVs have been researched in the existing studies, one-third of which cited behavioral theories, while the rest did not. A total of seven factors with behavior theories are screened out that significantly affect the acceptance intention, including perceived ease of use, attitude, social norm, trust, perceived usefulness, perceived risk, and compatibility. Six factors without behavior theories are summed up that affect AV acceptance, namely safety, performance-to-price value, mobility, value of travel time, symbolic value, and environmentally friendly. We found that people in Europe and Asia have substantial differences in attitudes toward AVs and that safety is one of the most concerned factors of AVs by scholars and respondents. Public acceptance of the different types of AVs and consumers’ dynamic preferences for AVs are highlighted in the review too. The quality of literature is systematically assessed based on previously established instruments and tailored for the current review. The results of the assessment show potential opportunities for future research, such as the citation of behavior theories and access to longitudinal data. Additionally, the experimental methods and the utilization of mathematical and theoretical methods could be optimized.

Keywords: public acceptance; autonomous vehicles; dynamic preference (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (43)

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